Jochen Cals

Professor

University of Maastricht

Netherlands

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About

Jochen Cals is a Professor at Maastricht University in the Netherlands. His research focuses on primary care, particularly in areas related to respiratory infections, antibiotic prescribing practices, and the use of digital health technologies. With recent publications exploring topics such as diagnostic prediction models using AI and patient access to medical records, he actively contributes to enhancing healthcare delivery and decision-making processes.

Articles (19)

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2025

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2022

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2022

Collaborators (11)

Paul Savelkoul

University of Maastricht

NETHERLANDS

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Ciska Hoving

University of Maastricht

NETHERLANDS

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Roderick P Venekamp

Associate Professor

University Medical Center Groningen

NETHERLANDS

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Mathie Leers

Professor Data-driven decisionmaking in Healthcare

Open Universiteit

NETHERLANDS

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Patricia M. Stassen

Maastricht University Medical Centre

NETHERLANDS

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Christian Hoebe

Professor and Chair Department

University of Maastricht

NETHERLANDS

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Eefje de Bont

Assistant Professor and GP

Maastricht University Medical Centre

NETHERLANDS

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Otto Maarsingh

Professor of General Practice

Amsterdam University Medical Centers

NETHERLANDS

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Rik Crutzen

University of Maastricht

NETHERLANDS

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Maarten Lambert

Utrecht University

NETHERLANDS

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Stella Heemskerk

University of Maastricht

NETHERLANDS

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Jochen Cals

Research Interests

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About

Articles (19)

Long-term prognosis of adults with moderately severe SARS-CoV-2 lower respiratory tract infection managed in primary care: Prospective cohort study

Diagnostic Prediction Models for Primary Care, Based on AI and Electronic Health Records: Systematic Review

Perceptions, facilitators and barriers of digital interdisciplinary consultation: a qualitative study

Adherence to antibiotic prescribing guidelines in Dutch primary care: an analysis of national prescription data on ear and respiratory tract symptoms and conditions among 384 general practices

Relevant determinants of Dutch patients’ informed decision-making and use of online access to medical records

Development and validation of a risk prediction model for hospital admission in COVID-19 patients presenting to primary care.

Comparing visual and automated urine dipstick analysis in a general practice population

Enhancing Patient Understanding of Laboratory Test Results: Systematic Review of Presentation Formats and Their Impact on Perception, Decision, Action, and Memory

Prospective diagnostic accuracy study of history taking and physical examination for adults with vertigo in general practice: study protocol

Machine learning for risk stratification in the emergency department (MARS-ED) study protocol for a randomized controlled pilot trial on the implementation of a prediction model based on machine learning technology predicting 31-day mortality in the emergency department

Knowledge, attitudes and practices around urinary tract infections of general practitioners in the Netherlands: a cross-sectional internet survey

Patients’ Experiences, Expectations, Motivations, and Perspectives around Urinary Tract Infection Care in General Practice: A Qualitative Interview Study

The Effects of Online Access to General Practice Medical Records Perceived by Patients: Longitudinal Survey Study

General Practitioner Use of e-Consultation to Consult Hospital Specialists: Interview Study to Obtain Physician’s Perceptions About Digital Interprofessional Communication

Patient online access to general practice medical records: A qualitative study on patients’ needs and expectations

Head-to-head comparison of 19 prediction models for short-term outcome in medical patients in the emergency department: a retrospective study

Physician-Targeted Interventions in Antibiotic Prescribing for Urinary Tract Infections in General Practice: A Systematic Review.

Trends in antibiotic prescribing in Dutch general practice and determinants of nonprudent antibiotic prescriptions.

Prevalence, pathophysiology, prediction and health-related quality of life of long COVID: study protocol of the longitudinal multiple cohort CORona Follow Up (CORFU) study

Collaborators (11)

Paul Savelkoul

Ciska Hoving

Roderick P Venekamp

Mathie Leers

Patricia M. Stassen

Christian Hoebe

Eefje de Bont

Otto Maarsingh

Rik Crutzen

Maarten Lambert

Stella Heemskerk

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